Geomechanics and Geophysics for Geo-Energy and Geo-Resources (Apr 2024)

Investigation of three-dimensional model reconstruction and fractal characteristics of crack propagation in jointed sandstone

  • Ziqi Liu,
  • Lulin Zheng,
  • Yujun Zuo,
  • Hao Liu,
  • Yuanjiang Hou,
  • Zehua Zhu,
  • Zhibin Hao,
  • Xiaokun Wang,
  • Gang Huang

DOI
https://doi.org/10.1007/s40948-024-00797-3
Journal volume & issue
Vol. 10, no. 1
pp. 1 – 16

Abstract

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Abstract The presence of random joints, cracks, and other defects significantly affects the meso-damage mechanism and macro-mechanical behavior of the rock. This study employed micro-CT scanning, digital image processing (DIP), and the rock failure process analysis system (RFPA3D) to reconstruct a genuine mesostructure, creating a three-dimensional (3D) numerical model of jointed sandstone. Under uniaxial stress, this model facilitated the meso-damage evolution process of prefabricated cracks in sandstone with varying dip angles. Additionally, the influence of jointed sandstone heterogeneity and prefabricated cracks with various dip angles on its failure mode and meso-damage mechanical properties were investigated. Utilizing the MATLAB platform, a 3D box dimension algorithm was developed to analyze the fractal characteristics of the mesodamage evolution in the sample. This algorithm enabled the quantitative characterization of the meso-damage evolution of sandstone. This study categorized three types of sandstone final failure modes: composite shear failure, shear failure along the joint surface, and tensile failure. Additionally, linear variations in the elastic modulus and compressive strength of the jointed sandstone were observed with increasing prefabricated fracture inclination, highlighting significant anisotropy. The presence of joints was found to induce and control the failure mode of sandstone. The meso-damage evolution process of sandstone was described in terms of the fractal dimension, indicating that more severe damage corresponded to a larger fractal dimension. This approach offers a novel statistical method for studying the progression of rock damage.

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